建立早期肝内胆管细胞癌（ICC）患者癌症特异性生存（CSS）的Nomogram预后预测模型，并验证其预测效能。

本研究从美国国立癌症研究所监测、流行病学及结局项目数据库（SEER）中筛选出943例早期ICC患者资料。按照7∶3比例随机分为训练组（663例）和验证组（280例）。训练组采用单因素及多因素Cox分析筛选独立危险因素，并建立基于独立危险因素的预后Nomogram模型。通过一致性指数（C-index）、ROC曲线、校准曲线验证Nomogram模型的准确性。采用决策分析曲线（DCA）来评价Nomogram模型的临床实用性，并与美国癌症联合委员会（AJCC）分期进行比较。根据Nomogram模型计算的总分对患者进行风险分层，Kaplan-Meier生存曲线分析模型的分层效果。

Cox回归分析显示，年龄、性别、婚姻状态、肿瘤直径、组织学分级、手术及放疗是早期ICC患者CSS的独立影响因素（HR=1.364，1.237，0.555，1.269，1.350，0.244，0.587；P<0.05）。基于危险因素构建患者CSS的Nomogram预测模型，训练组C-index为0.724，验证组为0.676；训练组及验证组1、3、5年ROC曲线的曲线下面积（AUC）均大于0.7。校准曲线分析显示，Nomogram预测结果具有良好的一致性。DCA分析显示，Nomogram模型具有良好的临床应用前景。与AJCC分期相比，该模型准确度和临床应用价值较高。建立风险分层系统，患者分为高、中、低危险组。Kaplan-Meier生存曲线分析显示，患者低、中、高危组的1年CSS率分别为88.4%、65.5%和35.5%，3年CSS率分别为63.4%、32.0%和7.6%，5年CSS率分别为48.2%、20.4%和4.5%，3组间CSS率差异有统计学意义（χ²=332.27，P<0.05）。

基于SEER数据库成功构建早期ICC预后Nomogram模型，该模型较传统AJCC分期有更好的预测效能，且可对患者生存风险进行分层分析。

To establish a Nomogram prognostic model for the cancer-specific survival (CSS) of patients with early intrahepatic cholangiocarcinoma (ICC) and to validate the predictive efficacy.

Clinical data of 943 patients with early ICC were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database of American National Cancer Institute (NCI). According to the ratio of 7∶3, they were randomly divided into the training (n=663) and validation groups (n=280). In the training group, the independent risk factors were screened by univariate and multivariate Cox's regression analyses, anda Nomogram prognostic model was established based on these independent risk factors. The accuracy of this model was validated by C-index, receiver operating characteristic (ROC) curve and calibration curve. The clinical utility of the Nomogram model was assessed by decision curve analysis (DCA) and compared with the American Joint Committee on Cancer (AJCC) staging. According to the total score calculated by Nomogram model, all patients were subjected to the risk stratification. The effect of risk stratification was evaluated by Kaplan-Meier survival curve.

Cox's regression analysis showed that age, sex, marital status, tumor diameter, histological grading, surgery and radiotherapy were the independent influencing factors for the CSS of patients with early ICC (HR=1.364, 1.237, 0.555, 1.269, 1.350, 0.244, 0.587; P<0.05). Based on these independent risk factors, the Nomogram prediction model of CSS patients was established. In the training group, the C-index was 0.724, and 0.676 in the validation group. The area under the ROC curve (AUC) at 1, 3 and 5 years exceeded 0.7 in two groups. The calibration curve analysis demonstrated that the predictive results of Nomogram model were in good agreement. DCA analysis revealed that Nomogram model had high clinical utility. Compared with the AJCC staging, this model yielded higher accuracy and clinical application value. A risk stratified system was established, and all patients were divided into the high, middle and low risk groups. Kaplan-Meier survival curve showed that the 1-year CSS in the low, middle and high risk groups were 88.4%, 65.5% and 35.5%, 63.4%, 32.0% and 7.6% for the 3-year CSS, and 48.2%, 20.4% and 4.5% for the 5-year CSS, respectively. Significant differences were observed in the CSS among three groups (χ²=332.27, P<0.05).

Based on the SEER database, the Nomogram prognostic model for early ICC has been successfully established. Compared with conventional AJCC staging, this model yields higher predictive efficiency, which can also deliver stratified analysis of survival risk.